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We examine the dynamic role of education and experience as determinants of wages. It is hypothesised that an employee’s education is an important signal to the employer initially. Over time, the returns to schooling should decrease with labour market experience and increase with initially unobserved ability, since the employer gradually obtains better information on the productivity of an employee. Replicating US studies using data from a large German panel data set (GSOEP), we find no evidence for the employer learning hypothesis for Germany. Differentiating blue-collar and white-collar workers and estimating quantile regressions, however, leads to the conclusion that employer learning takes place for blue-collar workers at the lower end of the wage distribution. We further show, that information on the productivity of an employee is to a large extend private.

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We analyze empirically the effects of urban agglomeration on Italian college graduates' work possibilities as entrepreneurs three years after graduation. We find that each 100,000 inhabitant-increase in the size of the individual's province of work reduces the chances of being an entrepreneur by 0.2-0.3 per cent. This result holds after controlling for regional fixed effects and is robust to instrumenting urbanization. Province's competition, urban amenities and dis-amenities, cost of labor, earning differentials between employees and self-employed workers, unemployment rates and value added per capita account for 40 per cent of the negative urbanization penalty. Our result cannot be explained by the presence of negative large-city differentials in returns to education either. In fact, as long as they succeed in entering the largest markets, young entrepreneurs are able to reap-off the benefits of urbanization externalities: every 100,000-inhabitant increase in the province's population raises entrepreneurs' net monthly income by 0.2-0.3 per cent.

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In the transition to a market economy, the Russian workforce underwent a wrenching period of change, with excess supply of some industrial skills coexisting with reports of skill shortages by many enterprises. This paper uses data from the Russia Competitiveness and Investment Climate Survey and related local research to gain insights into the changing supply and demand for skills over time, and the potential reasons for reported staffing problems and skill shortages, including labor turnover, compensation policies and the inhibiting effects of labor regulations. It discusses in-service training as an enterprise strategy for meeting staffing and skill needs, and presents evidence on the distribution, intensity and determinants of in-service training in Russia. It investigates the productivity and wages outcomes of in-service training, and the supportive role of training in firms’ research and development (R&D) and innovative activities. A final section concludes with some policy implications of the findings.

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We show how significant may be the difference in the estimated returns to education in Poland conditional on the measure of wages used and the estimation approach applied. Combining information from two different Polish surveys from 2005 and taking advantage of the Polish microsimulation model (SIMPL) we demonstrate how different the results can be depending on whether we use net or gross, and monthly or hourly wages, and show how important selection correction is for the conclusion. While there are several papers examining the wage equation in Poland, so far none of them has provided a comprehensive analysis of the effects of using different methods and the issue of selection-correction in the estimation of the wage equation in Poland has not been examined in detail. Annual rates of return to university education for men vary from 6.7 per cent to 9.7 per cent and for women from 8.0 per cent to 13.4 per cent when we compare results using net monthly wages without correcting for labor market selection to those from a selection corrected specification using gross hourly wages. We also demonstrate that simple linear estimation performs relatively well for men in comparison to our preferred selection corrected estimation, while using family demographics as exclusion restrictions seems to be the 'second best' in the case of the wage equation estimation for women.

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Using an internet collected dataset, we will provide some empirical evidence on the information that Dutch high school students possess before their decision on tertiary education participation. The sample is prone to selective participation and high attrition, but we detect little systematic effects and inconsistent reporting of probability distribution is not more frequent than in controlled settings. We find little support for patterns that one would expect from individuals having private information. Girls expect substantially lower earnings in all schooling scenarios, but implicit rate of returns do not differ from those anticipated by boys. We find no evidence of expected risk compensation.

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We use a quantile regression framework to investigate the degree to which work-related training affects the location, scale and shape of the conditional wage distribution. Human capital theory suggests that the percentage returns to training investments will be the same across the conditional wage distribution. Other theories - whether based on imperfections in the labour market or on skill-mix heterogeneity - suggest that this need not be the case. Using the first six waves of the European Community Household Panel, we investigate these issues for private sector men in 10 European Union countries. Our results show that, for the vast majority of countries, investment in training yields similar percentage returns across the conditional wage distribution. Only Belgium was an outlier in this respect. However, our results do indicate that there are considerable differences in mean returns to training across countries

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This paper examines the wage returns to qualifications and academic disciplines in the Greek labour market. Exploring wage responsiveness across various degree subjects in Greece is interesting, as it is characterised by high levels of graduate unemployment, which vary considerably by field of study, and relatively low levels of wage flexibility. Using micro-data from recently available waves (2002-2003) of the Greek Labour Force Survey (LFS), the returns to academic disciplines are estimated by gender and public/private sector. Quantile regressions and cohort interactions are also used to capture the heterogeneity in wage returns across the various disciplines. The results show considerable variation in wage premiums across the fields of study, with lower returns for those that have a marginal role to play in an economy with a rising services/shrinking public sector. Educational reforms that pay closer attention to the future prospects of university disciplines are advocated.

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In this paper we utilise microsimulation techniques in the form of an income generation model and a tax/benefit model to estimate both the fiscal and net private return to education at a marginal level. This is carried out empirically using Irish data across the period 1987-2005 and is the first study to utilise these techniques in such a manner. The results indicate that a more generous tax/benefit system, combined with a greater state burden of the cost of education over this period may have helped increase the individual's return to education, while reducing the state return from investing in education. The methodology employed allows us to specifically analyse the impact of various components of the tax/benefit system upon these returns across time and show the role of income tax changes upon the return to education for the individual and the state.

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This paper contains a survey of the recent literature devoted to the returns to schooling within a dynamic structural framework. I present a historical perspective on the evolution of the literature, from early static models set in a selectivity framework (Willis and Rosen, 1979) to the recent literature, stimulated by Keane and Wolpin (1997), and which uses stochastic dynamic programming techniques. After reviewing the literature thoroughly, I compare the structural approach with the IV (experimental) approach. I present their commonalities and I also discuss their fundamental differences. To get an order of magnitude, most structural estimates reported for the US range between 4% and 7% per year. On the other hand, IV estimates between 10% and 15% per year are often reported. The discrepancy prevails even when comparable (if not identical) data sets are used. The discussion is focused on understanding this divergence. The distinction between static and dynamic model specifications is a recurrent theme in the analysis. I argue that the distinction between the IV approach and the structural approach may be coined in terms of a trade off between behavioral and statistical assumptions. For this reason, and unless one has very specific knowledge of the true data generating process, it is neither possible, nor sensible, to claim which approach to estimation is more flexible. More precisely, I show that structural and IV approaches differ mainly at the level of (i) the compatibility of the underlying models with truly dynamic behavior, (ii) the role of heterogeneity in ability and tastes, (iii) the consideration of post-schooling opportunities, and (iv) the specification (and interpretation) of the Mincer wage equation.

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Using the Canadian General Social Survey we compute returns to post-secondary education relative to high-school. Unlike previous research using Canadian data, our dataset allows us to control for ability selection into higher education. We find strong evidence of positive ability selection into all levels of post-secondary education for men and weaker positive selection for women. Since the ability selection is stronger for higher levels of education, particularly for university, the difference in returns between university and college or trades education decreases slightly after accounting for ability bias. However, a puzzling large gap persists, with university-educated men still earning over 20% more than men with college or trades education. Moreover, contrary to previous Canadian literature that reports higher returns for women, we document that the [Ordinary Least Squares] OLS hourly wage returns to university education are the same for men and women. OLS returns are higher for women only if weekly or yearly wages are considered instead, because university-educated women work more hours than the average. Nevertheless, once we account for ability selection into post-secondary education, we generally find higher returns for women than for men for all wage measures as a result of the stronger ability selection for men.

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